By: Richard L. Smith
Artificial intelligence is increasingly being used to help make real health-care decisions — from predicting which treatments patients might need to helping decide what services insurers will cover.
That shift is coming to New Jersey, and public health experts say it brings both potential benefits and serious concerns.
According to reporting from New Jersey Monthly, academic researchers and health-care leaders across the state are exploring how AI can improve care, speed diagnosis, and help doctors focus more on patients rather than administrative tasks.
AI tools are already being used in hospitals and research centers to analyze medical records, support personalized treatment plans, and assist clinicians in identifying critical findings from scans and tests faster than manual review alone.
These applications can improve workflow efficiency and, in some cases, enhance early detection and tailored care for individuals facing serious illness.
At the same time, a major shift underway nationally could directly affect New Jersey residents enrolled in Medicare. Federal health agencies are planning a pilot program that will use AI to support decisions about whether Medicare will cover certain procedures and services.
Critics of the program warn that using algorithms for prior authorization or coverage decisions — even if intended to reduce unnecessary care, risks introducing delays or denials that may be hard for patients and doctors to challenge.
This “AI in coverage decisions” model is rooted in broader trends where insurers and government payers rely on automated systems to review claims and authorize services, a practice that already draws scrutiny for its potential to slow care and create barriers for patients.
Potential concerns cited by health policy analysts include:
• Delays in care — Algorithms filtering for “low-value” services could slow approvals for necessary procedures, particularly when patients or providers must appeal automated decisions.
• Lack of transparency — Proprietary models may not clearly explain why a decision was made, leaving patients and doctors uncertain about how to respond.
• Risk of bias — Emerging research suggests that AI models sometimes recommend different care based on socioeconomic or demographic factors in their training data, potentially worsening disparities.
At the same time, proponents argue smarter use of AI can reduce clinician burnout by handling data-heavy tasks, speed diagnosis, and help personalize treatments more precisely than conventional methods, benefits that could improve outcomes for many patients when tools are used under strict human supervision.
Whether AI’s growing role in medical decision-making will ultimately help or harm patients in New Jersey depends on how these systems are governed, how transparent they are, and whether strong human oversight remains at the center of care decisions.
Patients, advocates, and clinicians alike are calling for safeguards that preserve access, fairness, and accountability as this technology becomes more deeply embedded in the health system.